A Comparative Study of Single Input and Dual Input Power System Stabilizer by Hybrid Evolutionary Programming

被引：0

作者：

Chatterjee, A. ^{[1
]}

Ghoshal, S. P. ^{[2
]}

Mukherjee, V. ^{[3
]}

机构：

[1] Asansol Engn Coll, Dept Elect Engn, Asansol, India

[2] Natl Inst Technol, Elect Engn Dept, Durgapur, India

[3] Indian Sch Mines, Elect Engn Dept, Durgapur, India

来源：

2009 WORLD CONGRESS ON NATURE & BIOLOGICALLY INSPIRED COMPUTING (NABIC 2009) | 2009年

关键词：

Conventional power system stabilizer; dual input power system stabilizer; genetic algorithm; hybrid evolutionary programming; Sugeno fuzzy logic; GAINS;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this paper, a comparative transient performance of single-input conventional power system stabilizer (CPSS) and dual-input power system stabilizer (PSS), namely PSS4B is analyzed. The optimal parameters of both the CPSS and PSS4B are obtained with the help of hybrid evolutionary programming (HEP) technique. Step 1% perturbation in reference voltage and/or mechanical power input is applied to obtain the simulation results. It is revealed that the system transient performance of PSS4B equipped system model is better than CPSS equipped counter part for all on-line and off-line conditions, step changes in reference voltage and/or mechanical power input, during/after clearing of system faults. For on-line, off-nominal operating conditions, Sugeno fuzzy logic (SFL) is adopted to explore its adaptive and fast yielding features.

引用

页码：1046 / +

页数：2

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